The millennials (those born between 1980 and 2000) were the first ones to have grown up in a fully digital age.  The centennials (those born after 2000) will find it difficult to survive in the era of Big Data without having a minimum exposure to the STEM (Science, Technology, Engineering and Mathematics) subjects, whatever their professional or occupational choices (even ballet dancing will require mathematical literacy!)  Educators are now talking about the need for “humanics” for all who reach the tertiary level of education.  This means combining the humanities (which is indispensable for developing critical thinking skills, effective communication and the ability to relate one human discipline to another) with the study of the quantitative disciplines like mathematics and the sciences.  I, for one, have been advocating for decades that a liberal arts curriculum should include an introduction to the Calculus and Matrix algebra, the required knowledge of which is no longer limited to those going to pursue the STEM professions.  All the social sciences, for example, require a deep knowledge of statistics and mathematical reasoning.

         In his magisterial lecture entitled “The Many Faces of Counting,” Dr. Mariano points out the big difference between counting material things and counting human beings: “When it is people we are counting:  when I’m counted, I have a sense it’s the whole ‘me’ that’s being singled out, even if it’s by way of a property I have.”  That means that in any study where human beings are the subject of counting, they cannot be considered just as mere numbers but as intelligent and free creatures of God.  The second point he stresses is that counting is a human act, whenever it is done purposely, and will exhibit a multidimensional character. He illustrates this multidimensional character by demonstrating how the word “count” is embedded in English through a surprisingly wide array of metaphors and idiomatic expressions.  Among the notable ones he enumerates are:

         -The word count itself, which technically has the same sense when applied to stones as to people, but becomes more complex in the latter, not in terms of the act itself, but by implicating a host of other issues surrounding it.

         -The phrase count as, “What is to count as one?” which asks for the counting concept that initiates counting.

         -The idiomatic expression “Count me in,” and its correlative “Count me out,” as well as derivatives like “You can count on me,” or “Don’t count on it.”

         -Then, the important word accountable, as in “Do be accountable for your misdeed,” which comes from a prefixed form of late Latin computare, “calculate,”

         -And, finally, I count, as in “Don’t I count?” which carries a sense of value.

         Dr. Mariano elaborates on what are the complications that arise from the above mentioned various “faces of counting.”  Let me just focus on the fact that counting often entails sensitive decisions.  According to him, few will understand in philosophical, logical, let alone data-analytic terms, everything that a ‘counting concept’ is.  Most people, however, are capable of figuring out when decisions are being made about what is to “count as one.” He gave the colorful (pun intended) example of the US census of 1787 during which the question arose whether negro slaves were to be counted.  The problem had nothing to do with simple arithmetic. A political issue was involved.  The Northern and Southern States knew that the strength of their claim on political power and federal funds depended on the numbers.  The South was also insisting that slaves, though considered as property, had to answer for their misdeeds, like other human beings, which would not be the case were they only property—it would be the property owners who would be jailed.  The compromise was to count the negro slaves, not as one, but 3/5. 

         As Dr. Mariano points out, in the current debates leading to the 2020 US census, the same concerns about what is to count as one are being expressed.  Latino and Arab immigrants want to be recognized for the sake of their respective communities, but they are afraid that their data would fall in the hands of law enforcement agencies and be used to target them, especially in these days of anti-immigrant sentiments.  And for the first time, the LGBT community are lobbying to have gender preference included in the count.  It is quite clear from these examples that the question about what is to count as one is undeniably implicated in discrimination issue. The decision about “what’s-to-count-as-one?” prerequisite to counting is often supplied by a human decision which can be biased.  Clearly, if bias had been operative in the process of picking out and collecting data, the outcome will inevitably support consequences less favorable to some classes of people:  bias in, bias out! 

           Another glaring example of the moral limits to quantitative analysis is found in current efforts to develop predictive software that can project, from analyzing text messages, emails, and social media files the behavior patterns of certain groups of people, such as serial criminals, voters, or consumers.  When decision or policy makers believe that they can predict behavior, the next obvious step is to try and change it for one’s vested interests.  As Dr. Mariano comments: “We are concerned when we hear of Facebook, Google and Netflix developing software capable of inserting subliminal cues in their advertisement to turn users where and when they are most vulnerable.  Or when we hear of political campaigns using sophisticated methods not only to predict who the supporters are but to focus effort on the “persuadables”—voters who are more susceptible to being persuaded to count themselves among the followers of particular politicians.”  I personally have knowledge of certain experts in trolling that used social media to influence certain segments of the Philippine population to vote for President Duterte in the last presidential elections.  I am glad that the Facebook management decided to remove hundreds of politically-motivated trolls from their website.   (To be continued).